108 lines
3.8 KiB
TeX
108 lines
3.8 KiB
TeX
%% SCRAP: experiments/campaigns/l8_validation/README
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%% SOURCE: docs/working/experiments/campaigns/l8_validation/README.md
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%% STATUS: CURRENT
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%% FITS: experiments/ch-l8-map
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%% EDITORIAL: lifted — prose rewritten to press voice
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\section{L8 Jacquard Mode Selector Validation Experiment}
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This experiment validates the L8 Jacquard mode selector by comparing
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dynamic adaptive mode switching against static optimal configurations across
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five workload types. Its empirical basis is the $2^7$ factorial DoE
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(38{,}400 runs), which identified L1 and L4 as harmful and established
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workload-specific optimal configurations for L2, L3, L5, and L6.
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%% PATENT: the L8 Jacquard dynamic mode selector is patent-adjacent.
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%% Do not draft claims here.
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\subsection{Experimental Design}
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\textbf{Type:} $8 \times 5$ factorial design.
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\textbf{Independent variables:} control strategy (8 levels) and workload
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type (5 levels). \textbf{Primary dependent variables:} \texttt{ns\_per\_word}
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and \texttt{cv}.
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\subsubsection{Control Strategies}
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\begin{center}
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\begin{tabular}{llrrrrrrrl}
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\toprule
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Strategy & L1 & L2 & L3 & L4 & L5 & L6 & L7 & Description \\
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\midrule
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L8\_ADAPTIVE & 0 & rt & rt & 0 & rt & rt & 1 & Dynamic switching \\
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C0\_BASELINE & 0 & 0 & 0 & 0 & 0 & 0 & 1 & Minimal \\
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C4\_TEMPORAL & 0 & 0 & 1 & 0 & 0 & 0 & 1 & Decay only \\
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C7\_FULL\_INF & 0 & 0 & 1 & 0 & 1 & 1 & 1 & Full inference \\
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C9\_DIVERSE\_DECAY & 0 & 1 & 0 & 0 & 0 & 1 & 1 & Window + decay\_inf \\
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C11\_DIVERSE\_INF & 0 & 1 & 0 & 0 & 1 & 1 & 1 & Window + inference \\
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C12\_DIVERSE\_TEMP & 0 & 1 & 1 & 0 & 0 & 0 & 1 & Window + decay \\
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ALL\_ON & 0 & 1 & 1 & 0 & 1 & 1 & 1 & All except L1/L4 \\
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\bottomrule
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\end{tabular}
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\end{center}
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(rt = runtime-selected by L8 mode selector)
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\subsubsection{Workload Types}
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\begin{center}
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\begin{tabular}{lll}
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\toprule
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Workload & Characteristics & Expected L8 Mode \\
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\midrule
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STABLE & Predictable, repetitive & C0 or C4 \\
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DIVERSE & High entropy, mixed operations & C9, C11, or C12 \\
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VOLATILE & High CV, random branching & C1 or C7 \\
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TEMPORAL & Strong locality, nested loops & C4 or C12 \\
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TRANSITION & Phase shifts between workloads & Adaptive \\
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\bottomrule
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\end{tabular}
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\end{center}
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\subsection{Hypotheses}
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\begin{description}
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\item[H1 (Performance).] L8\_ADAPTIVE matches or exceeds the best static
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configuration per workload, within a 5\% margin.
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\item[H2 (Stability).] L8\_ADAPTIVE shows lower overall CV than any
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single static configuration across all workloads.
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\item[H3 (Adaptation).] The L8 mode distribution correlates with
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workload characteristics.
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\item[H4 (Generalization).] L8\_ADAPTIVE outperforms all static
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configurations on the TRANSITION workload.
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\end{description}
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\subsection{Running the Experiment}
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\begin{lstlisting}[language=bash]
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# Quick test (10 reps = 400 runs, ~8 minutes)
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cd experiments/l8_validation
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./run_l8_validation.sh 10
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# Standard validation (50 reps = 2,000 runs, ~40 minutes)
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./run_l8_validation.sh 50
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# High precision (100 reps = 4,000 runs, ~80 minutes)
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./run_l8_validation.sh 100
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\end{lstlisting}
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\subsection{Analysis}
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\begin{lstlisting}[language=bash]
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Rscript analyze_l8.R l8_validation_YYYYMMDD_HHMMSS
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\end{lstlisting}
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Expected plots: ANOVA interaction plot (strategy $\times$ workload), L8 mode
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distribution per workload, Pareto frontier (speed vs.\ stability), and
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convergence curves showing mode switches.
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\subsection{Success Criteria}
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\begin{enumerate}
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\item L8\_ADAPTIVE is at most 5\% slower than the best static
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configuration per workload.
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\item L8\_ADAPTIVE exhibits the lowest CV across all workloads.
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\item L8 mode selections align with expected workload-specific patterns.
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\item L8\_ADAPTIVE dominates all static configurations on TRANSITION.
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\end{enumerate}
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